Apparatus and method for color measurement and color grading of diamonds, gemstones, and the like

ABSTRACT

The present invention discloses method for color measurement and color grading of faceted gemstones, diamonds and the like. A novel three-step calibration insures an accurate spectral measurement of the sample inside the measurement integrating sphere. Using the method of the present invention, a computer provides measurement parameters calculated from the physical parameters of the measured sample, including, but not limited to, shape, dimensions, refractive index, intensity of fluorescence and cut grade. By means of the present invention, a computer then calculates the spectral reflectance and colorimetric data, and determines an average color grade by checking a look-up-table that represents the relationship between the CIELAB coordinate and the average color grade, and it also determines a true color grade based upon the average color grade and the physical parameters, using mathematical analyses and algorithms.

This is a divisional application of the copending application Ser. No. 11/678,564.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to method for color measurement and color grading of diamonds, gemstones and the like, and more particularly, method for measuring the spectral reflectance, for calculating the colorimetric data, and for determining the average color grade and the true color grade of a sample.

2. Description of the Related Art

Although color measurement is constant and accurate in general, color measurement and color grading of diamonds, gemstones and the like is difficult and often inaccurate for gemological researchers and jewelers because visual color grading involves many human factors and because faceted diamonds and gemstones are usually in irregular shapes and sizes. At best, all of the previous inventions and commercial instruments for color measurement of gemstones can only measure particular colors without determining the true meaning of the color.

An early invention for color grading of colorless to light yellow diamonds was disclosed by Shipley in U.S. Pat. No. 2,960,909. This invention passes a concentrated light beam through a diamond and onto a photocell connected to a microammeter. Based upon the ratio between a blue beam and minus-blue beam, a microammeter determines the color (grade) of the measured diamond.

Eickhorst (U.S. Pat. No. 3,794,424) uses a light conductor to directly illuminate the table of a gemstone and an optical transmitter to collect reflect light for the photocell to measure. However, this invention has a low color measurement accuracy below the requirement of the gem trade.

Hohberg et al. (U.S. Pat. No. 5,164,586) discloses an arrangement for color measurement of gemstones. This arrangement includes an integrating sphere and a dual channel spectrometer. The integrating sphere provides a uniform lighting for the gemstone, and transmitted light is measured. However, because transmitted light from pavilion to table is significantly different from the transmitted light through the side and the reflected light of faceted diamonds, this invention is neither practical nor useful.

Valente et al. (U.S. Pat. No. 5,615,005) discloses a gemstone evaluation system, with an integrating sphere, a band pass filter and a detector array. This system obtains the spectral reflectance of a complete image, and can provide a color image, a spectral measurement and colorimetric data for each individual pixel of the image. However, a band pass filter is not accurate or stable enough for the color measurement of gemstones. Practically, the system is also not accurate enough for color grading purposes.

Furthermore, two inventions previously disclosed by applicant are considered relevant to date by applicant, but do not anticipate nor teach the present invention. First, Liu (U.S. patent application Ser. No. 11/129,703) discloses optical filters for a CIE daylight simulator. The optical filters consist of two or more layers of colored glasses designed by optimization algorithms. When combined with a high color temperature incandescent, the filters can simulate a CIE standard daylight illuminant with a metamerism index B or better in the visible wavelength range. The colorimetric quality of the CIE daylight simulators at different color temperatures meets the CIE, ISO and ASTM standards for colorimetric and critical applications. In addition, Liu (U.S. application patent Ser. No. 11/322,431) also discloses a method and system for visual color grading of gemstones. The system can accurately generate a reference color to match the color of a gemstone under a standard viewing environment. Based on the matched color, the gemstone is assigned a color grade by a look-up-table representing the relationship between the color grades and the CIELAB coordinates.

Therefore, there remains a need for a method capable of accurate color measurement of gemstones, diamonds and the like, and more importantly, of precise color grading of same.

SUMMARY OF THE INVENTION

Accordingly, one object of the present invention is to provide a color measurement method that can accurately measure the color of gemstones, and more importantly, can determine color grades that are consistent with the grades obtained by visual color grading methods.

To achieve these and other advantages and in accordance with the purpose of the invention, as embodied and broadly described herein, the invention provides a method for measuring the color of gemstones, diamonds and like and determining the color grades accordingly. The method includes steps of inputting physical parameters, calculating the measurement parameters, measuring the spectral reflectance, calculating colorimetric data based on the spectral reflectance, determining the average color grade by checking the look-up-table, and determining the true color grade by using a mathematics method involving the average color grade and the physical parameters.

This method is implemented using an apparatus (described in a separate application) comprising of a spectrometer, a computer, and a dual integrating sphere measurement arrangement comprising a measurement integrating sphere, a sample integrating sphere, a measurement platform, a measurement window, a measurement window filter, a light source, a lens system, a light trap and a baffle. The spectral power distribution of the light source is converted in order to simulate the spectral power distribution of a CIE daylight illuminant. The light is integrated from the light source and which provides diffused light to illuminate the sample uniformly. The lens system in the measurement integrating sphere receives the reflected light from the sample, focuses the light into a fiber optic cable, and sends the light to the spectrometer through the fiber optic cable. The computer calculates the colorimetric data and determines the average color grade and the true color grade. The present invention allows the apparatus to measure the color of faceted and rough gemstones, diamonds and the like in any shape or size, and accurately determine the average color grade and the true color grade of same.

The present invention utilizes a novel three-step procedure for calibrating the apparatus. The three-step calibration procedure includes white calibration, black calibration and an additional dual integrating spheres calibration.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 (Canceled)

FIG. 2 (Previously presented) is a flowchart depicting the method of color measurement and color grading.

DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 2, a flowchart depicts the method of the present invention. The method includes the steps of the input of physical parameters 21, measurement parameter calculation 22, spectral measurement 23, color calculation 24, average color grading 25 by checking a look-up-table 26, and true color grading 27.

The first step of the method is to input physical parameters 21 into the computer. The parameters include the sample's shape, length, width, depth, refractive index, intensity of fluorescence and cut grade. Faceted gemstones can be in any shape, and it is impossible to list all of the shapes for the input 21. As an approximate approach, the input step 21 of the preferred embodiment only includes the most popular shapes, such as, but not limited to, round, oval, rectangle, marquise, and heart. Other shapes shall be substituted by the listed shapes with the most similar shapes. The shape of “princess cut,” for example, shall be substituted by the rectangle shape.

Length, width and depth are measured in units of millimeters. The refractive index of a gemstone can be measured by a refractometer or other physics methods. The refractive index can also be obtained by checking references, such as books and articles.

According to the preferred embodiment, the cut grade is arbitrarily quantified in a scale from 0 to 100 as an input parameter. On the cut grade scale, 100 represents the perfect cut grade, which refers to a cut where all incoming light will be totally reflected back through the table; 90-99 represents the cut grade of excellent; 80-89 represents the cut grade of very good; 70-79 represents the cut grade of good; 60-69 represents the cut grade of fair; 1-59 represents the cut grade of poor; and 0 represents rough gemstones without faceting and polishing. The higher the cut grade of a gemstone, the better the true color grade because there is more internal reflection. When the cut grade is 0 for a rough gemstone, its true color grade is the same as its average color grade. For a gemstone with two parallel surfaces, its cut grade is also assigned as 0, and again its true color grade is the same as its average color grade.

According to the preferred embodiment, the intensity of fluorescence is arbitrarily quantified in a scale from 0 to 100 as an input parameter. On the fluorescence intensity scale, 0 represents inert, which means no fluorescence; larger then 0 to 10 represents faint; 10 to 30 represents weak; 30 to 50 represents medium; 50 to 70 represents strong; 70 to 90 represent very strong; and 90 to 100 represents extreme. The higher the intensity of fluorescence is, the more intense the fluorescence is. The fluorescence includes that caused by both ultraviolet and visible light.

In the step of measurement parameters calculation 22, the parameters for controlling the spectrometer are calculated by mathematical algorithms using the physical parameters inputted in step 21. The mathematic algorithms are one or more mathematic methods including, but not limited to, complex numerical function, matrix transfer, finite element analysis, numerical analysis, artificial neural network, optimization, fuzzy logic, regression, possibility, and statistics. The calculated measurement parameters include, but are not limited to, integration time, samples to average, bandwidth, width of slit, boxcar width, and the voltage of the detector. In said step 22, the parameters for calculating the spectral reflectance are also calculated.

The measurement parameters calculated in the step 22 are sent to the spectrometer for the spectral measurement 23. The spectrometer uses the measurement parameters to set its measurement condition, and then to measure the spectral reflectance of the sample on the measurement window filter inside the sample integrating sphere. The spectrometer outputs a digital count file S(λ) for the spectral reflectance of the sample to the computer to calculate the spectral reflectance.

According to another aspect of the invention, two parameters called black calibration correction α and measurement integrating sphere correction κ are introduced for calculating the spectral reflectance of the sample. Both the black calibration correction α and the measurement integrating sphere correction κ are the function of the input parameters 21. As mentioned hereinabove, both the black calibration correction α and the measurement integrating sphere correction κ are calculated in the step of measurement parameters calculation 22.

The spectral reflectance of the sample is calculated by the equation:

$\begin{matrix} {{R(\lambda)} = \frac{{S(\lambda)} - {\alpha \; {B(\lambda)}} - {\kappa \; {{IS}(\lambda)}}}{{W(\lambda)} - {B(\lambda)}}} & \left( {{Equation}\mspace{14mu} 1} \right) \end{matrix}$

where λ is wavelength in nanometers, R(λ) is the spectral reflectance of the sample, S(λ) is the measured digital counts of the sample, W(λ) is the digital counts of the white calibration, B(λ) is the digital counts of the black calibration, IS(λ) is the digital counts of the integrating sphere calibration, a is the black calibration correction, and κ is the integrating sphere calibration correction.

Because the white standard tile for the white calibration cannot be 100% reflectance in the measurement wavelength range and the black standard tile cannot be 0% reflectance, the white calibration W(λ) and black calibration B(λ) can be further corrected for a higher accuracy. Accordingly, considering the white standard tile correction and black standard tile correction, the Equation 1 is changed to:

$\begin{matrix} {{R(\lambda)} = \frac{{S(\lambda)} - {\alpha \; {C_{2}(\lambda)}{B(\lambda)}} - {\kappa \; {{IS}(\lambda)}}}{{{C_{1}(\lambda)}{W(\lambda)}} - {{C_{2}(\lambda)}{B(\lambda)}}}} & \left( {{Equation}\mspace{14mu} 2} \right) \end{matrix}$

where C₁(λ) is the white standard tile spectral correction parameter and C₂(λ) is the black standard tile spectral correction parameter. The spectral reflectance of the white and black standard tiles can trace to that of the white and black standards at the National Institute of Standards and Technology in Gaithersburg, Md. The white and black standard tile spectral correction parameters can be calculated by the known spectral reflectance of the white and black standard tiles.

The spectral reflectance R(λ) obtained from the Equation 2 is used for calculating the colorimetric data in the step of color calculation 24. In the preferred embodiment, the calculated colorimetric data include L*, a*, b*, C*_(ab) and h_(ab) in the CIELAB color space. L* is the lightness, +a* represent red color and −a* represents green color, +b* represents yellow color and −b* represents blue color, C*_(ab) is the chroma or the saturation and h_(ab) is the hue angle.

The colorimetric data can also be expressed in other color spaces, including a CIELUV color space or a 1931 CIE color space. In a CIELUV color space, the colorimetric data includes L*, u*, v*, saturation S_(uv) and hue-angle h_(uv). In a 1931 CIE color space, the colorimetric data includes x, y, and Y coordinates.

The CIELAB coordinates L*, a* and b* are used in the next step of average color grading 25 to assign a color grade. The computer checks the look-up-table to locate the color grade corresponding to the L*, a* and b* coordinate of the sample. The look-up-table represents the relationship between the color grades and the CIELAB color coordinate (L*, a*, b*). Each CIELAB color coordinate (L*, a*, b*) corresponds to a color grade, but each color grade covers a large volume of color space. The color grade obtained in this step 25 is outputted as the average color grade. The average color grade is also sent to the next step of true color grading 27 to determine a true color grade.

According to another aspect of the invention, the preferred embodiment determines the true color grade from the average color grade and the input parameters 21. The true color refers to the “key color” defined by the Gemological Institute of America (hereinafter GIA) for the faceted colored gemstones, and refers to the “characteristic color” (also defined by GIA) for the colored diamonds.

The true color grade is determined by the average color grade and the physical parameters using the mathematics analyses and algorithms including, but not limited to, finite element analysis, numerical analysis, artificial neural network, optimization, fuzzy logic and regression. The true color grade corresponds to a visual color grading performed by human color graders under controlled illuminating and viewing geometries and under standard environments.

Other embodiments of the invention will appear to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and the description to be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims. 

1-12. (canceled)
 13. A method for determining average color grade and true color grade, comprising the steps of: inputting the physical parameters of a sample into a computer; calculating measurement parameters for measuring spectral reflectance of the sample; measuring the spectral reflectance of the sample; calculating colorimetric data, based upon, among other things, measured spectral reflectance; determining the average color grade using the colorimetric data; and determining the true color grade using the average color grade and physical parameters.
 14. The method according to claim 13 wherein the physical parameters of the sample include, but are not limited to, shape, length, width, depth, refractive index, intensity of fluorescence, and cut grade.
 15. The method according to claim 13 wherein said step of calculating the measurement parameters includes using the computer to calculate the measurement parameters, which measurement parameters include, but are not limited to, measurement time, samples for average, width of the slit, voltage of the detector and range of wavelength.
 16. The method according to claim 13 wherein the step of calculating the measurement parameters includes using one or more algorithms selected from the group consisting of complex numerical function, matrix transfer, finite element analysis, numerical analysis, artificial neural network, optimization, fuzzy logic, regression, possibility, and statistics.
 17. The method according to claim 13 wherein the step of measuring the spectral reflectance of the sample includes using a measuring means configured to receive light of spectral reflectance from the sample, separate said light into spectrum, convert the intensity of the spectrum into digital counts, and output digital counts to said computer.
 18. The method according to claim 13, wherein said measuring means is selected from the group consisting of a spectrometer, spectrophotometer, spectral imaging system, spectral graphic system and spectroradiometer.
 19. The method according to claim 13, wherein said measuring means is a colorimeter with R, G and B detectors.
 20. The method according to claim 13 wherein the step of calculating colorimetric data includes the steps of calculating the spectral reflectance of the sample and then using the spectral reflectance to calculate colorimetric data in a color space.
 21. The method according to claim 20, wherein the step of calculating the spectral reflectance of the sample is by the following equation: ${R(\lambda)} = \frac{{S(\lambda)} - {\alpha \; {C_{2}(\lambda)}{B(\lambda)}} - {\kappa \; {{IS}(\lambda)}}}{{{C_{1}(\lambda)}{W(\lambda)}} - {{C_{2}(\lambda)}{B(\lambda)}}}$ where is wavelength in nanometers, R(λ) is the spectral reflectance of the sample, S(λ) is a measured digital count of the sample, W(λ) is a digital count of white calibration, B(λ) is a digital count of black calibration, IS(λ) is a digital count of integrating sphere calibration parameter, α is a black calibration correction parameter, κ is an integrating sphere calibration correction parameter, C₁(λ) is a white standard tile spectral correction parameter and C₂(λ) is a black standard tile spectral correction parameter.
 22. The method according to claim 13 wherein the step of determining the average color grade includes checking a look-up-table to find a color grade corresponding to the colorimetric data in a color space and assigning said color grade as the average color grade.
 23. The method according to claim 13 wherein the step of determining the true color grade includes assigning a true color grade based upon the colorimetric data in a color space of the average color grade, the physical parameters, and mathematic analyses and algorithms including, but not limited to, matrix transfer, finite element analysis, numerical analysis, artificial neural network, optimization, fuzzy logic, regression, possibility, and statistics.
 24. The method according to claim 20 or claim 22 or claim 23 wherein the color space is selected from the group consisting of a CIELAB color space including colorimetric data L*, a*, b*, C*_(ab) and h_(ab), a CIELUV color space including colorimetric data L*, u*, v*, Suv and huv, and a CIE(x, y)color space including colorimetric data x, y and Y. 